Reconstruction And Visualization Of Edge Surfaces Within 3D Images

Along with the rapid development of 3D image technology and its application in biology, medicine, a lot of 3D biomedical images have been produced. The necessary of processing and analyzing these 3D images promotes the development of analysis and visualization of 3D images. Since the sep-like edge surfaces usually correspond to the edge surface included the anatomical structure within 3D images. So reconstruction and visualization of the step-like edge surface become an important issue in the research field.3D step like images can be understood by consecutive implicit surface contained in its sections based the definition of 3D regular data. As a result, this dissertation discusses detection, reconstruction and visualization of step-like edge surface within 3D images. Firstly, a new surface detecting and tracing algorithm is proposed in this dissertation based the connectivity characteristics of the edge surface. In the algorithm, we first detect the edge cubes include edge surface sheet. During the tracing process, we use region growing algorithm based connectivity principles of the two adjacent cubes, and obtain all the other edge cubes included edge surface. The result of the experiments demonstrates that the algorithm overcomes the flaws obviously, and can acquire high-precision (sub-voxel accuracy) edge surface. In addition, because of the great number of 3D volume data, we employ some effective methods to reduce the space complexity and time complexity.Secondly, the dissertation is to proposed on interactive edge surface selection and extraction algorithm. In the algorithm, operators first select ROI edge surface in the 2D slices areas, then the selected 2D areas are mapped to 3D ROI areas automatically. We can detect part of edge cubes in the 3D ROI, and trace the edge surface models in which the users are interested. It is known for all of us that the doctors often would rather acquire...